Real-Time Analytics Platform

Architecture Views

21 views, in reading order. Every view ships three ways: an HTML page, an SVG that re-opens in diagrams.net fully editable, and draw.io source.

Twenty-one views of an Azure real-time analytics platform, ordered as one argument: what sits inside the boundary, what the parts are, where the data lives, what happens at runtime, how it is operated, and why it is safe. The load-bearing decision is that the durable event log and its immutable bronze capture are the system of record — every store downstream of them is rebuildable, which is what makes a 5-second freshness target survivable when something breaks.

Context and scope

The boundary: who produces events, who consumes analytics, and what the platform deliberately does not do.

01 System Context Who produces events, who consumes analytics, and which enterprise systems the platform depends on — the boundary of scope with no internal components shown. HTML page SVG draw.io

02 High-Level Architecture The end-to-end shape in one picture: managed ingestion into an Event Hubs durable log, Databricks stream processing, and Azure Data Explorer as the hot analytics store behind a governed query surface. HTML page SVG draw.io

Structure

The deployable parts, how they depend on each other, every interface, and where the tenant boundary sits.

03 Layered Architecture What depends on what. Dependencies point downward only; platform services are consumed by every layer above them. HTML page SVG draw.io

04 Container Architecture The deployable units, the technology each runs on, and the protocol on every hop — what an engineering team actually builds and owns. HTML page SVG draw.io

05 Integration and Interface Catalogue Every way the platform touches another system, with protocol, direction and cadence — the single page an enterprise architect can review against the estate. HTML page SVG draw.io

06 Tenancy and Workload Isolation Where the tenant boundary sits at each layer, and how one tenant's traffic or one team's ad-hoc query is prevented from degrading everybody else. HTML page SVG draw.io

Data

What is stored, in which tier, for how long, under whose ownership, and how the event contract is governed.

07 Event Data Flow Where data comes from, what format and cadence it moves in, what is retained at each hop, and where an event goes when it cannot be processed. HTML page SVG draw.io

08 Storage Zones, Tiering and Retention Every store the platform owns, grouped by who owns it and whether it can be rebuilt — the view that answers what happens if a given store is lost. HTML page SVG draw.io

09 Analytics Data Model The tables the hot store actually holds, their keys and cardinality — including the dead-letter and schema-contract tables that most models omit. HTML page SVG draw.io

10 Schema Contract Governance How an event schema changes without a redeployment and without breaking a consumer — the lane-by-lane path from proposal to retirement. HTML page SVG draw.io

Runtime

What actually happens per event: processing, windowing, the latency budget, the query path, and correction after the fact.

11 Stream Processing Pipeline What each micro-batch does, stage by stage, and exactly where the delivery guarantee is established. HTML page SVG draw.io

12 Windowing and Late-Arriving Events Each window type against what state it keeps, when it emits, and what happens to an event that arrives after its window has closed. HTML page SVG draw.io

13 Event to Insight — Critical Path One event from SDK call to dashboard pixel, with the latency budget spent at each hop against the 5-second p95 target. HTML page SVG draw.io

14 Query and Serving Architecture How a query reaches an answer in under 2 seconds while dashboards, ad-hoc analysis and exports run concurrently without competing. HTML page SVG draw.io

15 Replay, Backfill and Correction How a defect discovered after the fact is corrected without taking the platform down or letting a consumer read a half-corrected table. HTML page SVG draw.io

Operations

Where it runs, how a change reaches production, how it is watched, and how it recovers.

16 Deployment and Infrastructure What runs where, which failure domains it spans, and what is actually standing by in the secondary region. HTML page SVG draw.io

17 CI/CD and Environment Promotion How a change reaches production, what stops a bad one at each gate, and how a streaming job is released without skipping an event. HTML page SVG draw.io

18 Observability and Service Level Objectives Which signal is collected at which stage, and which of them will page somebody — the matrix an SRE reads before accepting the service. HTML page SVG draw.io

19 Reliability and Recovery Loop The loop the platform runs when something goes wrong, and the point at which retained raw events turn a detection into a recovery. HTML page SVG draw.io

Assurance

Trust boundaries, what crosses them, and how producers and consumers prove who they are.

20 Security Architecture — Trust Zones Where the trust boundaries are, what crosses each one and under what authentication, and where an attacker with a stolen credential actually arrives. HTML page SVG draw.io

21 Identity and Access Flow Who proves what, to whom, in what order — for a machine producer publishing events and a human analyst running a query. HTML page SVG draw.io

Open svg/<view>.svg or drawio/<view>.drawio in draw.io Desktop or at app.diagrams.net to edit. The SVG carries the diagram inside it, so it is both the picture and the source. This folder is self-contained — copy it whole and every link still resolves.